Lack of specialist care is associated with increased morbidity and mortality in adult congenital heart disease: a population-based study.

AIMS: The aim of this study was to provide population-based data on the healthcare provision for adults with congenital heart disease (ACHD) and the impact of cardiology care on morbidity and mortality in this vulnerable population. METHODS AND RESULTS: Based on administrative data from one of the largest German Health Insurance Companies, all insured ACHD patients (<70 years of age) were included. Patients were stratified into those followed exclusively by primary care physicians (PCPs) and those with additional cardiology follow-up between 2014 and 2016. Associations between level of care and outcome were assessed by multivariable/propensity score Cox analyses. Overall, 24 139 patients (median age 43 years, 54.8% female) were included. Of these, only 49.7% had cardiology follow-up during the 3-year period, with 49.2% of patients only being cared for by PCPs and 1.1% having no contact with either. After comprehensive multivariable and propensity score adjustment, ACHD patients under cardiology follow-up had a significantly lower risk of death [hazard ratio (HR) 0.81, 95% confidence interval (CI) 0.67-0.98; P = 0.03) or major events (HR 0.85, 95% CI 0.78-0.92; P < 0.001) compared to those only followed by PCPs. At 3-year follow-up, the absolute risk difference for mortality was 0.9% higher in ACHD patients with moderate/severe complexity lesions cared by PCPs compared to those under cardiology follow-up. CONCLUSION: Cardiology care compared with primary care is associated with superior survival and lower rates of major complications in ACHD. It is alarming that even in a high resource setting with well-established specialist ACHD care approximately 50% of contemporary ACHD patients are still not linked to regular cardiac care. Almost all patients had at least one contact with a PCP during the study period, suggesting that opportunities to refer patients to cardiac specialists were missed at PCP level. More efforts are required to alert PCPs and patients to appropriate ACHD care.

Context in synthetic biology: Memory effects of environments with mono-molecular reactions.

Synthetic biology aims at designing modular genetic circuits that can be assembled according to the desired function. When embedded in a cell, a circuit module becomes a small subnetwork within a larger environmental network, and its dynamics is therefore affected by potentially unknown interactions with the environment. It is well-known that the presence of the environment not only causes extrinsic noise but also memory effects, which means that the dynamics of the subnetwork is affected by its past states via a memory function that is characteristic of the environment. We study several generic scenarios for the coupling between a small module and a larger environment, with the environment consisting of a chain of mono-molecular reactions. By mapping the dynamics of this coupled system onto random walks, we are able to give exact analytical expressions for the arising memory functions. Hence, our results give insights into the possible types of memory functions and thereby help to better predict subnetwork dynamics.

A variational approach to moment-closure approximations for the kinetics of biomolecular reaction networks.

Approximate solutions of the chemical master equation and the chemical Fokker-Planck equation are an important tool in the analysis of biomolecular reaction networks. Previous studies have highlighted a number of problems with the moment-closure approach used to obtain such approximations, calling it an ad hoc method. In this article, we give a new variational derivation of moment-closure equations which provides us with an intuitive understanding of their properties and failure modes and allows us to correct some of these problems. We use mixtures of product-Poisson distributions to obtain a flexible parametric family which solves the commonly observed problem of divergences at low system sizes. We also extend the recently introduced entropic matching approach to arbitrary ansatz distributions and Markov processes, demonstrating that it is a special case of variational moment closure. This provides us with a particularly principled approximation method. Finally, we extend the above approaches to cover the approximation of multi-time joint distributions, resulting in a viable alternative to process-level approximations which are often intractable.

Frequency, Mortality, and Predictors of Adverse Outcomes for Endocarditis in Patients with Congenital Heart Disease: Results of a Nationwide Analysis including 2512 Endocarditis Cases.

BACKGROUND: Infective endocarditis (IE) represents a major complication in patients with congenital heart disease (CHD) and is associated with high morbidity and mortality. The aim of this study was to analyse the frequency and outcome of IE in contemporary CHD patients based on all IE hospital admissions in Germany over a 10-year period. METHODS: Based on data of all hospital admissions in Germany from 2009 to 2018, we identified all CHD cases with a diagnosis of IE. The data contained information on patient demographics, diagnoses, surgical procedures, and mortality. The primary endpoint of the study was endocarditis-associated mortality as well as major adverse events (defined as death or myocardial infarction, stroke, pulmonary embolism, sepsis, renal dialysis, resuscitation, or intubation). RESULTS: Overall, 309,245 CHD inpatient cases were included in the analysis (underlying heart defects of simple complexity 55%, moderate complexity 23%, and complex heart defects 22%, respectively). Of those, 2512 (0.8% of all inpatient cases) were treated for IE. The mortality rate of IE inpatient cases was 6% with a major adverse events rate of 46%, and 41.5% of cases required surgical intervention. The overall IE associated mortality was lower in adult CHD cases compared to the 153,242 in adult IE cases without CHD (7.1% vs. 16.1%, p < 0.001). After adjustments using multivariable logistic regression analysis, the presence or complexity of CHD was not associated with the outcomes. Meanwhile, age, male sex, and co-morbidities emerged as significant predictors of adverse outcomes. CONCLUSIONS: IE accounts for a minority of CHD related hospitalizations but remains a deadly disease, and major adverse events are common in this setting. Due to different demographic and co-morbidity spectrums, adult CHD patients tend to have better survival prospects when compared to non-CHD IE patients. Acquired co-morbidities emerged as the main predictors of adverse outcomes.

Eye Tumors in Childhood as First Sign of Tumor Predisposition Syndromes: Insights from an Observational Study Conducted in Germany and Austria.

Retinoblastoma and other eye tumors in childhood are rare diseases. Many eye tumors are the first signs of a genetic tumor predisposition syndrome and the affected children carry a higher risk of developing other cancers later in life. Clinical and genetic data of all children with eye tumors diagnosed between 2013-2018 in Germany and Austria were collected in a multicenter prospective observational study. In five years, 300 children were recruited into the study: 287 with retinoblastoma, 7 uveal melanoma, 3 ciliary body medulloepithelioma, 2 retinal astrocytoma, 1 meningioma of the optic nerve extending into the eye. Heritable retinoblastoma was diagnosed in 44% of children with retinoblastoma. One child with meningioma of the optic nerve extending into the eye was diagnosed with neurofibromatosis 2. No pathogenic constitutional variant in DICER1 was detected in a child with medulloepithelioma while two children did not receive genetic analysis. Because of the known association with tumor predisposition syndromes, genetic counseling should be offered to all children with eye tumors. Children with a genetic predisposition to cancer should receive a tailored surveillance including detailed history, physical examinations and, if indicated, imaging to screen for other cancer. Early detection of cancers may reduce mortality.

Marginal process framework: A model reduction tool for Markov jump processes.

Markov jump process models have many applications across science. Often these models are defined on a state space of product form and only one of the components of the process is of direct interest. In this paper we extend the marginal process framework, which provides a marginal description of the component of interest, to the case of fully coupled processes. We use entropic matching to obtain a finite-dimensional approximation of the filtering equation, which governs the transition rates of the marginal process. The resulting equations can be seen as a combination of two projection operations applied to the full master equation so that we obtain a principled model reduction framework. We demonstrate the resulting reduced description on the totally asymmetric exclusion process. An important class of Markov jump processes are stochastic reaction networks, which have applications in chemical and biomolecular kinetics, ecological models, and models of social networks. We obtain a particularly simple instantiation of the marginal process framework for mass-action systems by using product Poisson distributions for the approximate solution of the filtering equation. We investigate the resulting approximate marginal process analytically and numerically.

ROC'n'Ribo: Characterizing a Riboswitching Expression System by Modeling Single-Cell Data.

RNA-engineered systems offer simple and versatile control over gene expression in many organisms. In particular, the design and implementation of riboswitches presents a unique opportunity to manipulate any reporter device in cis, executing tight temporal and spatial control at low metabolic costs. Assembled to higher order genetic circuits, such riboswitch-regulated devices may efficiently process logical operations. Here, we propose a hierarchical stochastic modeling approach to characterize an in silico repressor gate based on neomycin- and tetracycline-sensitive riboswitches. The model was calibrated on rich, transient in vivo single-cell data to account for cell-to-cell variability. To capture the effect of this variability on gate performance we employed the well-known ROC-analysis and derived a novel performance indicator for logic gates. Introduction of such a performance measure is necessary, since we aimed to assess the correct functionality of the gate at the single-cell level-a prerequisite for its further adaption to a genetic circuitry. Our results may be applied to other genetic devices to analyze their efficiency and ensure their correct performance in the light of cell-to-cell variability.